Research on BP Neural Network Model for Water Demand Forecasting and its Application

Author:

Sun Yue Feng1,Chang Hao Tian2,Miao Zheng Jian2

Affiliation:

1. Tianjin Polytechnic University,

2. Tianjin University,

Abstract

It is difficult to determine a proper neurons number of the mid-layer when using the BP neural network for water demand forecasting. Aiming at the problem, the BP neural network is presented in this paper for water demand forecasting. A suitable neurons number in the mid-layer is calculated based on the empirical formula method and trial and error method. A certain basin in China is taken as a case study. The results indicate that the mean relative error is 2.42%. The water consumption is 42.8 billion m3 in 2015 and 43.6 billion m3 in 2030 in the study area. The results are useful for water resources planning and management.

Publisher

Trans Tech Publications, Ltd.

Reference15 articles.

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2. Weng Wenbin, Wang Zhongjing and Zhao Jianshi. Modern water resources planning – theory, method, and technology. Tsinghua University Press, Beijing (2004) (In Chinese).

3. Shaofeng Yuan, Jun Lu. Journal of Agricultural Mechanization Research Vol. 10 (2003) pp.5-8 (In Chinese).

4. Rongfeng Li. Shanxi Hydrotechnics Vol. 10(4) (2003) pp.50-53 (In Chinese).

5. Xiaoling Wang, Yuefeng Sun, Lingguang Song and Chuanshu Mei. Journal of Environmental Management Vol. 90(8) (2009), pp.2612-2619 (In Chinese).

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